Jake Loosararian: Robots should prioritize data collection on efficiency, the impact of Nvidia’s dominance in the range of hardware, and the important role of decision making in future development.

Important takeaways

• Robots should prioritize data collection to improve performance and decision making.
• Industries such as energy and defense are increasingly using robots for efficiency.
• The future of robotics is promising, but safety and reliability through determinism are important.
• Consolidation around Nvidia reduces the diversity of hardware, which contributes to the development of AI.
• Robots can improve efficiency in industries with high energy costs and frequent shutdowns.
• GPUs are becoming essential for scaling AI applications, especially for conversation-based models.
• The difference in hardware is due to proprietary software programs.
• CUDA is outdated on modern systems, indicating the need for updated GPU software.
• Various systems improve computing flexibility and robustness.
• Businesses want flexibility in hardware to avoid vendor lock-in.
• The pragmatic impact of AI and robotics is focused on sectors such as energy and defense.
• Determinism in robotics ensures safety and reliability in AI systems.
• The rise of conversation-based models has furthered the importance of the GPU in AI.

Guest introduction

Jake Loosararian is the CEO and founder of Gecko Robotics, a company that uses purpose-built robotics and AI to inspect critical infrastructure across energy, defense, and manufacturing. In 2012 as a student at Grove City College, he built his first robot that climbed the wall in the bedroom to solve the continuous downtime in the power plant, launching the company in 2013. Gecko now manages more than 500,000 critical assets of Fortune 100 partners and the US Air Force and Navy, reaching a valuation of 25 billion in June.5.

The role of data in robotics

• The concept of gathering information and data using robots to help drive better results

  – Jake Loosararian

• Robots shouldn’t just be built to build; they must serve a purpose in the collection of data.
• Data-driven robots could prevent a materialized future in the industry.

• If you build robots just to build robots… it leads to a commoditized future

  – Jake Loosararian

• Understanding the role of data is critical to improving infrastructure performance.
• Robotics in infrastructure is about making decisions with data.

• The pragmatic impact of artificial intelligence… can create better decisions

  – Jake Loosararian

• Data collection is essential for improving efficiency in key areas.

Robots in power and defense

• The energy, oil, gas, and defense sectors are focusing on the pragmatic impact of robotics.

• Energy, oil and gas companies… are totally looking at how impactful robots can be

  – Jake Loosararian

• Robotics and the integration of AI are improving efficiency in these industries.
• The defense industry is exploring robotics for improved decision making.

• The military department is fully aware of how effective robots can be

  – Jake Loosararian

• Robots help to meet the challenges in industries with high energy costs.

• Robots can greatly improve the efficiency of industries facing high energy costs

  – Jake Loosararian

• The focus is on how robots can drive better results in power and protection.

The future of robots and determinism

• The future of robotics is promising but requires a focus on determination.

• I am very excited and optimistic… what the future holds for robots

  – Jake Loosararian

• Determinism ensures safety and reliability in robotics applications.

• The key is determination… maybe that’s where we’re lacking a bit

  – Jake Loosararian

• Safety and reliability are important in the rapidly evolving field of robotics.
• Determinism balances innovation and safety in robotics.
• The focus on determinism addresses potential security concerns in AI.
• Ensuring reliability in robots is essential for future development.

Hardware diversity and Nvidia’s dominance

• The integration around Nvidia reduces the diversity of hardware in AI development.

• Most of the world is truly integrated into the Nvidia platform

  – Jake Loosararian

• There is a need for more hardware vendors to encourage innovation in AI.

• We are looking for more hardware vendors in the space

  – Jake Loosararian

• Nvidia’s dominance influences the range of AI hardware options.
• The diversity of computing platforms is critical to fostering innovation in AI.
• The current state of AI hardware requires more competition.
• Integration limits the capabilities of separate AI hardware solutions.

The importance of GPUs in AI

• GPUs are still essential for scaling AI applications.

• GPUs have taken over the world… their side is huge

  – Jake Loosararian

• The rise of conversation-based models has driven the importance of GPUs.
• GPUs improve the computational power of AI technology.
• The role of GPUs is essential for computational tasks in AI.
• The emergence of AI technology has increased the demand for GPUs.
• GPUs are essential for developing AI computing power.
• The importance of GPUs in AI continues to grow with technological advances.

Isolation in hardware compatibility

• The isolation comes from the lack of a unifying software layer.

• Hardware companies don’t get along… they build software for their chips

  – Jake Loosararian

• Proprietary systems contribute to hardware compatibility issues.
• Competitive forces between hardware companies lead to fragmentation.
• Proprietary software solutions contribute to industry fragmentation.
• Compatibility issues arise from the lack of a unified approach.
• The impact of proprietary software on hardware systems is significant.
• Partitioning affects the overall efficiency of hardware systems.

Need for updated GPU software

• CUDA is outdated for modern systems and productive AI.

• CUDA… is the shining star of system software for GPUs but it is 20 years old

  – Jake Loosararian

• There is a need for GPU software innovation for current technology trends.
• Existing GPU software may not meet the needs of modern developments.
• The relevance of CUDA is questioned in the context of new technologies.
• Modern applications require updated GPU software solutions.
• The evolution of technology requires the development of GPU software.
• The need for updated software is critical to improving AI capabilities.

Heterogeneous systems in computing

• Various systems improve the flexibility and scalability of computing.

• You get these different plans when you have different properties

  – Jake Loosararian

• Different hardware architectures that interact with each other enhance computing capabilities.
• Different systems are important in modern computer architecture.
• The impact of various systems on business dynamics is significant.
• Businesses benefit from the flexibility offered by various systems.
• Changes in computing architecture have an impact on technology investment.
• Different systems play an important role in the future development of computing.

Avoiding vendor lock in hardware options

• Businesses desire the ability to choose between different hardware systems.

• It gives businesses choice… they want choice so they can use other systems

  – Jake Loosararian

• Avoiding vendor lock-in is an important concern for businesses.
• Flexibility in choosing technology is important for businesses.
• Businesses want to avoid becoming dependent on a single hardware vendor.
• The ability to choose different systems improves business flexibility.
• Vendor lock-in causes technology adoption challenges.
• Businesses are prioritizing flexibility in hardware decisions to drive innovation.